Computer systems are continuing to grow in popularity and are frequently interconnected with other computer systems via networks, such as local area networks (LANs) and the Internet. Features such as electronic mail (email), instant messaging, and project collaboration encourage the use of computer systems coupled to networks. These features allow users to, for example, communicate with other users, retrieve information, and share common documents.
In some situations, a user may need to interact with an unfamiliar person, an unfamiliar department, or an unfamiliar group. In other situations, a user may desire to learn how another person, department, or group is related to the user. For example, a user may want to talk to another person in an organization, but has never been introduced to that other person. In this situation, the user would like to know if there is a common person or a common group with which both the user and the other person are associated. In another example, a user may want to learn about a particular project, but doesn't know if they have any relationship to the project.
Attempting to discover these types of relationships manually is time-consuming and inefficient. For example, if a user asks a large group of people whether they know a particular person, that user spends a great deal of their time communicating with these people, and takes time away from each person that is contacted. Further, attempting to manually search through various organizational charts, mailing lists, and other information to discover a relationship between two people (or between a person and a group) is time-consuming and may not accurately discover all relationships.
It would be desirable to provide an improved approach to identifying one or more relationships between two points in an environment.